116 citations · 249 across the 11 of their papers we have counts for
11 papers
Evaluating Open-Weight Large Language Models for Structured Data Extraction from Narrative Medical Reports Across Multiple Use Cases and Languages
Douwe J. Spaanderman, Karthik Prathaban, Petr Zelina +20
Large language models (LLMs) are increasingly used to extract structured information from free-text clinical records, but prior work often focuses on single tasks, limited models,…
Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review
Chuang Zhu, Shengjie Liu, Zekuan Yu +15
For invasive breast cancer, immunohistochemical (IHC) techniques are often used to detect the expression level of human epidermal growth factor receptor-2 (HER2) in breast tissue t…
Adversarial Learning with Multiscale Features and Kernel Factorization for Retinal Blood Vessel Segmentation
Farhan Akram, Vivek Kumar Singh, Hatem A. Rashwan +4
In this paper, we propose an efficient blood vessel segmentation method for the eye fundus images using adversarial learning with multiscale features and kernel factorization. In t…
An Efficient Solution for Breast Tumor Segmentation and Classification in Ultrasound Images Using Deep Adversarial Learning
Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser +5
This paper proposes an efficient solution for tumor segmentation and classification in breast ultrasound (BUS) images. We propose to add an atrous convolution layer to the conditio…
SLSNet: Skin lesion segmentation using a lightweight generative adversarial network
Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Farhan Akram +8
The determination of precise skin lesion boundaries in dermoscopic images using automated methods faces many challenges, most importantly, the presence of hair, inconspicuous lesio…
Fence GAN: Towards Better Anomaly Detection
Cuong Phuc Ngo, Amadeus Aristo Winarto, Connie Kou Khor Li +3
Anomaly detection is a classical problem where the aim is to detect anomalous data that do not belong to the normal data distribution. Current state-of-the-art methods for anomaly…
Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural Network
Vivek Kumar Singh, Hatem A. Rashwan, Santiago Romani +8
Mammogram inspection in search of breast tumors is a tough assignment that radiologists must carry out frequently. Therefore, image analysis methods are needed for the detection an…
REFUGE CHALLENGE 2018-Task 2:Deep Optic Disc and Cup Segmentation in Fundus Images Using U-Net and Multi-scale Feature Matching Networks
Vivek Kumar Singh, Hatem A. Rashwan, Adel Saleh +4
In this paper, an optic disc and cup segmentation method is proposed using U-Net followed by a multi-scale feature matching network. The proposed method targets task 2 of the REFUG…
Retinal Optic Disc Segmentation using Conditional Generative Adversarial Network
Vivek Kumar Singh, Hatem Rashwan, Farhan Akram +7
This paper proposed a retinal image segmentation method based on conditional Generative Adversarial Network (cGAN) to segment optic disc. The proposed model consists of two success…
Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification
Vivek Kumar Singh, Santiago Romani, Hatem A. Rashwan +9
This paper proposes a novel approach based on conditional Generative Adversarial Networks (cGAN) for breast mass segmentation in mammography. We hypothesized that the cGAN structur…
SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks
Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Farhan Akram +8
Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma. In this paper, we present a robust deep learning SLS model, so-called SL…